We propose a large scale terrain adaptive compression method with high compression rate in this paper by using integer wavelet transform combined with restricted quadtree triangulation based on the terrain variation characteristic. By taking advantage of the efficient computing and multi-resolution attributes of our algorithm, we can decompress the wavelet coefficients which indicate the terrai...

Classification of multi class images is very enviable for different recognition. This is affected by many factors such as noise, blur, low illumination, complex background, occlusion etc. Noise is one of the major factors causing degradation of the classification performance. This paper proposes an efficient method for classification of multi class object images which are corrupted by Gaussian ...

Fourier transform has been shown to be a powerful tool in many area of science. However, there is another class of unitary transforms, the wavelet transforms, which are as useful as the Fourier transform. Wavelet transforms are used to expose the multi-scale structure of a signal and very useful for image processing and data compression. In this paper, we construct quantum algorithms for Haar w...

this paper presents a new multi-sensor data fusion method based on the combination of wavelettransform (wt) and extended kalman filter (ekf). input data are first filtered by a wavelettransform via daubechies wavelet “db4” functions and the filtered data are then fused based onvariance weights in terms of minimum mean square error. the fused data are finally treated byextended kalman filter for...

Gait is a biometric feature and gait recognition has become a challenging problem in computer vision. New wavelet velocity moments have been developed to describe and recognize gait. Wavelet moments are translation, scale and rotation invariant. Wavelet analysis has the trait of multi-resolution analysis, which strengthens the analysis ability to image subtle feature. According with the psychol...

A dynamically adaptive numerical method for solving multi-dimensional evolution problems with localized structures is developed. The method is based on the general class of multi-dimensional second-generation wavelets and is an extension of the second-generation wavelet collocation method of Vasilyev and Bowman to two and higher dimensions and irregular sampling intervals. Wavelet decomposition...

In this paper, a hybrid method is proposed for multi-channel electroencephalograms (EEG) signal compression. This new method takes advantage of two different compression techniques: fractal and wavelet-based coding. First, an effective decorrelation is performed through the principal component analysis of different channels to efficiently compress the multi-channel EEG data. Then, the decorrela...

Aiming at the characteristics which variable air volume air conditioning system is multi-variable, nonlinear and uncertain system, normal fuzzy neural network is hard to meet the requirements which dynamic control of multi-variable. In this paper, we put forward a recursive neural network predictive control strategy based on wavelet neural network model. Through recursive wavelet neural network...

The properties of wavelet transform, viz. the ability to identify and efficiently represent temporal/spatial coherent flow structures, self-adaptiveness, and de-noising, have made them attractive candidates for constructing multi-resolution variable fidelity schemes for simulations of turbulence [10]. Stochastic Coherent Adaptive Large Eddy Simulation (SCALES) [6] is the most recent wavelet-bas...